Perbandingan Kombinasi Genetic Algorithm – Simulated Annealing dengan Particle Swarm Optimization pada Permasalahan Tata Letak Fasilitas
Abstract: This article aims to
compare the performance of combination of Genetic Algorithm-Simulated Annealing
(GA-SA) with Particle Swarm Optimization (PSO) to solve facility layout
problem. GA-SA in this article consist of two algorithms, GA-SA I and GA-SA II,
with a different mutation rule. PSO uses fuzzy particle swarm concept to
represent solution from each particle. Two criteria to analyze all algorithms
performance are moment of movement and computational time. Experiments show
that GA-SA II has the best performance in minimization both criteria
Keywords: Genetic Algorithm,
Simulated Annealing, Particle Swarm Optimization, fuzzy particle swarm,
facility layout problem
Penulis: Isabella Leo
Setiawan, Herry Christian Palit
Kode Jurnal: jptindustridd100064
